I
INTRODUCTION TO DECISION
SUPPORT SYSTEMS
Decision Support Systems for Business Intelligence
by Vicki L. Sauter
Copyright © 2010 John Wiley & Sons, Inc.
INTRODUCTION
Virtually everyone makes hundreds of decisions each day. These decisions range from the
inconsequential, such as what to eat for breakfast, to the significant, such as how best to get
the economy out of a recession. All other things being equal, good outcomes from those
decisions are better than bad outcomes. For example, all of us would like to have a tasty,
nutritional breakfast (especially if it is fast and easy), and the country would like to have
a stable, well-functioning economy again. Some individuals are "lucky" in their decision
processes. They can muddle through the decision not really looking at all of the options
or at useful data and still experience good consequences. We have all met people who
instinctively put together foods to make good meals and have seen companies that seem to
do things wrong but still make a good profit. For most of us, however, good outcomes in
decision making are a result of making good decisions.
"Good decision making" means we are informed and have relevant and appropriate
information on which to base our choices among alternatives. In some cases, we support
decisions using existing, historical data, while other times we collect the information,
especially for a particular choice process. The information comes in the form of facts,
numbers, impressions, graphics, pictures, and sounds. It needs to be collected from various
sources, joined together, and organized. The process of organizing and examining the
information about the various options is the process of modeling. Models are created to
help decision makers understand the ramifications of selecting an option. The models can
range from quite informal representations to complex mathematical relationships.
For example, when deciding on what to eat for a meal, we might rely upon historical
data, such as those available from tasting and eating the various meal options over time and
Decision Support Systems for Business Intelligence
by Vicki L. Sauter
Copyright © 2010 John Wiley & Sons, Inc.
4
INTRODUCTION
our degree of enjoyment of those options. We might also use specially collected data, such
as cost or availability of
the
options. Our model in this case might be simple: Select the first
available option that appeals to
us.
Or, we might approach it with a more complex approach:
Use linear programming to solve the "diet problem" to find the cheapest combination of
foods that will satisfy all the daily nutritional requirements of a person.
1
In today's business world, we might use models to help refine our understanding
of what and how our customers purchase from us to improve our customer relationship
management. In that case we might collect information from point-of-sale systems for all
of our customers for multiple years and use data-mining tools to determine profiles of
our customers. Those profiles could in turn profile information about trends with which
managers could change marketing campaigns and even target some marketing campaigns.
The quality of the decision depends on the adequacy of the available information, the
quality of the information, the number of options, and the appropriateness of the modeling
!
The diet problem was one of the first large-scale optimization problems solved using modern
modeling techniques. The Army wished to
find
the cheapest way to provide the necessary nutrition
to the
field
soldiers. The National Bureau of Standards solved the problem with the simplex method
(which was new then) with 9 equations and 77 variables. To solve the problem, it took nine clerks
using hand-operated calculators 120 days to find the optimal solution. For more information on
the diet problem, including a demonstration of the software, check the NEOS page at http://www-
neos.mcs.anl.gov/CaseStudies/dietpy/WebForms/index.html.
Equifax provides DSS and supporting databases to many of America's Fortune 1000 companies
which til 1 u
w
these businesses to m ak
e
m ore effecti ve and profi tabl
e
busi n es
s
dec;
i si on s. The sy stem
allows users access to more than 60 national databases, mapping software, and analysis tools so
that users can define and analyze its opportunitie
s in a geographic area.
The tool enables retailers, banks, and other businesses to display trade areas and then to
analyze demographic attributes. In particular
, this DSS integrates customer information with cur-
rent demographi
c and locational data. For example, Consumer-Facts'
M
, offers information about
spending patterns of more than 400 products and services in more than 15 major categories, with
regional spending patterns incorporated
. Further, it provides five-year projections that reflect the
impact of dynamic economic and demographi
c conditions, such as income, employment
, popu-
lation, and household changes, on consumer spending that can be integrated with a corporation'
s
own customer information,
This coupling of data and analysis of reports, maps, and graphs allows decision makers to
consider questions of customer segmentation and targeting; market and site evaluation; business-
to-business marketing; product distributio
n strategies; and mergers, acquisitions, and competitive
analysis. For example, the DSS facilitates consideration of crucial, yet difficult questions such as:
• Who are my best customers and where are they located?
• Which segments respond positively to my marketing campaign?
• How will the addition of
a
new site impact my existing locations?
• How can
T
analyze and define my market potential?
• How can I estimate demand for my products and services accurately?
• What impact will an acquisition have on my locations?
• How is the competition impacting my business
?
INTRODUCTION
effort available at the time of the decision. While it is
not
true that more information (or
even more analysis) is better, it is true that more of
the
appropriate type of information (and
analysis) is better. In fact, one might say that to improve the choice process, we need to
improve the information collection and analysis processes.
Increasingly corporations are attempting to make more informed decisions to improve
their bottom
lines.
Some refer to these efforts to use better information and better models to
improve decision making as business intelligence. Others refer to it as analytics. In either
case,
the goal is to bring together the right information and the right models to understand
what is going on in the business and to consider problems from multiple perspectives so as
to to provide the best guidance for the decision maker.
One way to accomplish the goal of bringing together the appropriate information and
models for informed decision making is to use decision support systems (DSS). Decision
support systems are computer-based systems that bring together information from a variety
of sources, assist
in
the organization and analysis of information, and facilitate the evaluation
of assumptions underlying the use of specific models. In other words, these systems allow
decision makers to access relevant data across the organization as they need it to make
choices among alternatives. The DSS allow decision makers to analyze data generated from
transaction processing systems and other internal information sources
easily.
In addition,
DSS allow access to information external from the organization. Finally, DSS allow the
decision makers the ability to analyze the information in a manner that will be helpful to
that particular decision and will provide that support interactively.
So,
the availability of DSS provides the opportunity to improve the data collection
and analyses processes associated with decision making. Taking the logic one step further,
the availability of DSS provides the opportunity to improve the quality and responsiveness
of decision making and hence the opportunity to improve the management of corpora-
tions.
Said differently, the DSS provides decision makers the ability to explore business
intelligence in an effective and timely fashion.
To see how DSS can change the way in which decisions are made, consider the
following example of
a
Manhattan court. Consider the problem. New York spends in excess
of
$3
billion each year on criminal justice and the number of jail beds has increased by over
110%
in 20 years. In Manhattan, in particular, developers have spent billions of dollars
refurbishing neighborhoods and providing good-quality living, business, and entertainment
areas.
Yet people continue not to feel safe in them, and minor crimes depreciate the quality
Biologists working at the university of Missouri-St Louis and trie Missouri Botanical Gardens
have used a specialized kind of
DSS
called a geographic information system (GIS) to test hy-
potheses
in
phytogeographic
studies.
The
GIS
allows for greater sophistication in studies of spatial
components, such as the movement patterns of fruit-eating birds. For
example,
the Loiselle Lab
at UM-St. Louis considered the Atlantic forests of Brazil and bird migration using a GIS, They
modeled
the historic
distributions of birds in
this
region using
a GIS
and digitalized environmental
layers from the National Atlas of
Brazil.
These historic distributions were compared
to
the present
forest coverage
to
estimate the impact of the vast deforestation of
this
area.
This allowed Loiselle
to estimate the original habitat and the implications of its reduction. This, in turn, allowed the
researchers to consider
a
wide range of
options
that impacted biodiversity conservation decisions
of
these
forests.
INTRODUCTION
of life for residents. Furthermore, the likelihood of repeat offenses is high; over
40%
of the
defendants seen in a year already have three or more convictions.
While clearly there is a problem, those facts (that crime exists, that enormous amounts
of money are spent, and that people do not feel safe) are examples of bad
outcomes,
not
necessarily bad decisions. However, three facts do suggest the quality of
the
decision could
be improved:
• Criminal justice workers know very little about the hundreds of thousands of people
who go through the New York court systems.
• There has been little creative thinking about the sanctions judges can use over time.
• Most defendants get the same punishment in the same fashion.
Specifically, they suggest with more information, more modeling capabilities, and better
alternative generation tools that better decisions, which could result in superior outcomes,
might be achieved.
In this case, citizens, court officials, and criminal justice researchers noted the problem
of information availability and have developed a process to address it for "quality-of-life"
crimes, such as shoplifting and street hustling. Specifically, the city, landlords, and federal
funding jointly created a new court and located the judge in the same building as city
health workers, drug counselors, teachers, and nontraditional community service outlets
to increase the likelihood of the court working with these providers to address the crime
problem innovatively. The centerpiece of this effort is a DSS that provides judges with
more and better information
as well as
a better way for processing that information so as
to make an impact on the crime in Manhattan.
This example does illustrate some of the important characteristics of a DSS. A DSS
must access data from a variety of sources. In this court example, the system accesses the
arresting officer's report, including the complaint against the offender and the court
date.
In
addition, the DSS provides access to the defendant's criminal record through connections
with the New York Division of Criminal Justice. These police records are supplemented
with information gained by an independent interviewer either at the police precinct or at
the courthouse. These interviewers query the defendant regarding their lifestyle, such as
access to housing, employment status, health conditions, and drug dependencies. Finally,
an intermediary between the court and the services available, called a court resource
coordinator, scans the person's history, makes suggestions for treatment, and enters the
information into the system.
A second characteristic of a DSS is that it facilitates the development and evaluation
of a model of the choice process. That is, the DSS must allow users to transform the
enormous amount of "data" into "information" which helps them make a good decision.
The models may be simple summarization or may be sophisticated mathematical models.
In this case, the modeling takes on a variety of forms. The simple ability to summarize
arrest records allows judges to estimate recidivism if no intervention occurs. Further, the
summarization of lifestyle information encourages the development of a treatment model.
In addition, with the DSS, the judge can track community service programs and sites
to determine which is likely to be most effective for what kinds of offenses. Hence, the
judge can model the expected impact of the sanctions on a defendant with particular
characteristics. In other words, it can facilitate the evaluation of programs to determine if
there is a way to have greater impact on particular defendants or on a greater number of
defendants.
